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on Network Economics |
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Issue of 2017‒01‒22
three papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Akerlof, Robert; Holden, Richard |
| Abstract: | This paper explores the problem of assembling capital for projects. It can be difficult to assemble capital, when it is disaggregated, for a project that exhibits increasing returns. Small investors may be reluctant to participate, as they may question the ability of the project owner to raise the additional capital he requires. This suggests the possibility that agents with blocks of capital (capital that is already aggregated) might earn rents. Similarly, agents with "network capital" - that is, an ability to aggregate the capital of others - may earn rents. In this paper, we develop a theory of the rents attached to capital assembly, and discuss the implications for a range of issues from investment, to growth, to inequality. |
| Keywords: | increasing returns; inequality; investment; network capital |
| JEL: | D24 D30 D85 G30 L26 |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:11763&r=net |
| By: | Qin, Bei; Strömberg, David; Wu, Yanhui |
| Abstract: | This paper documents basic facts regarding public debates about controversial political issues on Chinese social media. Our documentation is based on a dataset of 13.2 billion blog posts published on Sina Weibo - the most prominent Chinese microblogging platform- during the 2009-2013 period. Our primary finding is that a shockingly large number of posts on highly sensitive topics were published and circulated on social media. For instance, we find millions of posts discussing protests and an even larger number of posts with explicit corruption allegations. This content may spur and organize protests. However, it also makes social media effective tools for surveillance. We find that most protests can be predicted one day before their occurrence and that corruption charges of specific individuals can be predicted one year in advance. Finally, we estimate that our data contain 600,000 government-affiliated accounts which contribute 4% of all posts about political and economic issues on Sina Weibo. The share of government accounts is larger in areas with a higher level of internet censorship and where newspapers have a stronger pro-government bias. Overall, our findings suggest that the Chinese government regulates social media to balance threats to regime stability against the benefits of utilizing bottom-up information. |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:11778&r=net |
| By: | Pablo Brañas-Garza; Angelo Antoci; Alexia Delfino; Fabio Paglieri; Fabrizio Panebianco; Fabio Sabatini |
| Abstract: | Evidence is growing that forms of incivility–e.g. aggressive and disrespectful behaviors, harassment, hate speech and outrageous claims–are spreading in the population of social networking sites’ (SNS) users. Online social networks such as Facebook allow users to regularly interact with known and unknown others, who can behave either politely or rudely. This leads individuals not only to learn and adopt successful strategies for using the site, but also to condition their own behavior on that of others. Using a mean field approach, we define anevolutionary game framework to analyse the dynamics of civil and uncivil ways of interaction in online social networks and their consequences for collective welfare. Agents can choose to interact with others–politely or rudely–in SNS, or to opt out from online social networks to protect themselves from incivility. We find that, when the initial share of the population of polite users reaches a critical level, civility becomes generalized if its payoff increases more than that of incivility with the spreading of politeness in online interactions. Otherwise, the spreading of self-protective behaviors to cope with online incivility can lead the economyto non-socially optimal stationary states |
| JEL: | C61 C73 D85 O33 Z13 |
| Date: | 2016–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:68800&r=net |